Optimization Algorithm of College Table Tennis Teaching Quality Based on Big Data

Abstract

In recent years, big data has quietly risen. Big data has been widely used in social practice. It has gradually formed a new trend and new trend of thinking that massive data catalyzes innovation and development, and regards data as big and respects objective data indicators. At present, with the continuous development of my country's sports industry, there is an increasing shortage of professional table tennis talents in society. Under this, many college students choose table tennis majors, making the college table tennis majors more and more popular. However, despite many college students participating in this industry, the teaching effect is not so ideal. The most important means of cultivating excellent table tennis talents is to reform teaching methods and innovate teaching methods. Selecting and cultivating the reserve forces of college student table tennis players, the two core links of the work of cultivating talents, has become an important scientific research topic. This article mainly discusses the deficiencies of the current education model based on the current status of the teaching quality of table tennis in colleges and universities in our country and the research situation of young athletes, combined with the optimization model of table tennis teaching in colleges and universities based on big data, and strives to break through the single dimension of traditional teaching mode,limitations such as method lag. This article conducts research on it through literature method and questionnaire method. Research shows that compared with the quality of the traditional teaching mode, the college table tennis teaching after optimizing the algorithm on the basis of big data has been improved overall.